Within-farm transmission dynamics of foot and mouth disease as revealed by the 2001 epidemic in Great Britain

Transoceanic pathogen transfer in the age of sail and steam

In the centuries following Christopher Columbus's 1492 voyage to the Americas, transoceanic travel opened unprecedented pathways in global pathogen circulation. Yet no biological transfer is a single, discrete event. We use mathematical modeling to quantify historical risk of shipborne pathogen introduction, exploring the respective contributions of journey time, ship size, population susceptibility, transmission intensity, density dependence, and pathogen biology. We contextualize our results using port arrivals data from San Francisco, 1850 to 1852, and from a selection of historically significant voyages, 1492 to 1918. We offer numerical estimates of introduction risk across historically realistic ranges of journey time and ship population size, and show that both steam travel and shipping regimes that involved frequent, large-scale movement of people substantially increased risk of transoceanic pathogen circulation.

Foot-and-Mouth Disease

Foot-and-mouth disease (FMD) is a viral infection of livestock that is an important determinant of global trade in animal products. The disease causes a highly contagious vesicular syndrome of cloven-hoofed animals. Successful control of FMD is dependent upon early detection and recognition of the clinical signs, followed by appropriate notification and response of responsible government entities. Awareness of the clinical signs of FMD amongst producers and veterinary practitioners is therefore the key in protecting US agriculture from the catastrophic impacts of an FMD outbreak. This review summarizes key clinical and epidemiologic features of FMD from a US perspective.

Epidemiological investigation of foot-and-mouth disease outbreaks in a Vietnamese bear rescue centre

Foot-and-mouth disease (FMD) outbreaks affecting Asiatic black bears (Ursus thibetanus) and a Malayan sun bear (Helarctos malayanus) were previously reported in 2011 in two housing facilities at a Vietnamese bear rescue centre. In this study, demographic data of all animals housed in the centre at the time of the outbreaks (n = 79) were collected. Blood samples drawn from 23 bears at different timepoints were tested for FMDV-specific antibodies targeting using a non-structural protein (NSP) ELISA and by virus neutralisation test (VNT). The relationship between seroconversion and clinical signs was explored and epidemic curves and transmission diagrams were generated for each outbreak, where FMD cases were defined as animals showing FMD clinical signs. Outbreak-specific attack rates were 18.75 and 77.77%, with corresponding basic reproduction numbers of 1.11 and 1.92, for the first and second outbreaks, respectively. Analyses of risk factors showed that after adjusting for sex there was strong evidence for a decrease in odds of showing clinical signs per year of age. All samples collected from bears before the outbreak tested negative to NSP and VNT. All cases tested positive to VNT following onset of clinical signs and remained positive during the rest of the follow up period, while only 6 out of 17 cases tested positive to NSP after developing clinical signs. Six animals without clinical signs were tested post outbreaks; five seroconverted using VNT and three animals were seropositive using NSP ELISA. This study provides initial epidemiological parameters of FMD in captive bears, showing that FMDV is easily spread between bears in close proximity and can cause clinical and subclinical disease, both of which appear to induce rapid and long-lasting immunity.

Analysis of within-pen and between-pen fenceline temporal contact networks in confined feedlot cattle

Though contact networks are important for describing the dynamics for disease transmission and intervention applications, individual animal contact and barriers between animal populations, such as fences, are not often utilized in the construction of these models. The objective of this study was to use contact network analysis to quantify contacts within two confined pens of feedlot cattle and the shared "fenceline" area between the pens at varying temporal resolutions and contact duration to better inform the construction of network-based disease transmission models for cattle within confined-housing systems. Two neighboring pens of feedlot steers were tagged with Real-Time Location System (RTLS) tags. Within-pen contacts were defined with a spatial threshold (SpTh) of 0.71 m and a minimum contact duration (MCD) of either 10 seconds (10 s), 30 seconds (30 s), or 60 seconds (60 s). For the fenceline network location readings were included within an area extending from 1 m on either side of the shared fence. "Fenceline" contacts could only occur between a steer from each pen. Static, undirected, weighted contact networks for within-pen networks and the between-pen network were generated for the full study duration and for daily (24-h), 6-h period, and hourly networks to better assess network heterogeneity. For the full study duration network, the two within-pen networks were densely homogenous. The within-pen networks showed more heterogeneity when smaller timescales (6-h period and hourly) were applied. When contacts were defined with a MCD of 30 s or 60 s, the total number of contacts seen in each network decreased, indicating that most of the contacts observed in our networks may have been transient passing contacts. Cosine similarity was moderate and stable across days for within pen networks. Of the 90 total tagged steers between the two pens, 86 steers (46 steers from Pen 2 and 40 steers from Pen 3) produced at least one contact across the shared fenceline. The total network density for the network created across the shared fenceline between the two pens was 17%, with few contacts at shorter timescales and for MCD of 30 s or 60 s. Overall, the contact networks created here from high-resolution spatial and temporal contact observation data provide estimates for a contact network within commercial US feedlot pens and the contact network created between two neighboring pens of cattle. These networks can be used to better inform pathogen transmission models on social contact networks.

Inferring transmission routes for foot-and-mouth disease virus within a cattle herd using approximate Bayesian computation

To control an outbreak of an infectious disease it is essential to understand the different routes of transmission and how they contribute to the overall spread of the pathogen. With this information, policy makers can choose the most efficient methods of detection and control during an outbreak. Here we assess the contributions of direct contact and environmental contamination to the transmission of foot-and-mouth disease virus (FMDV) in a cattle herd using an individual-based model that includes both routes. Model parameters are inferred using approximate Bayesian computation with sequential Monte Carlo sampling (ABC-SMC) applied to data from transmission experiments and the 2007 epidemic in Great Britain. This demonstrates that the parameters derived from transmission experiments are applicable to outbreaks in the field, at least for closely related strains. Under the assumptions made in the model we show that environmental transmission likely contributes a majority of infections within a herd during an outbreak, although there is a lot of variation between simulated outbreaks. The accumulation of environmental contamination not only causes infections within a farm, but also has the potential to spread between farms via fomites. We also demonstrate the importance and effectiveness of rapid detection of infected farms in reducing transmission between farms, whether via direct contact or the environment.

Quantifying the relationship between within-host dynamics and transmission for viral diseases of livestock

Understanding the population dynamics of an infectious disease requires linking within-host dynamics and between-host transmission in a quantitative manner, but this is seldom done in practice. Here a simple phenomenological model for viral dynamics within a host is linked to between-host transmission by assuming that the probability of transmission is related to log viral titre. Data from transmission experiments for two viral diseases of livestock, foot-and-mouth disease virus in cattle and swine influenza virus in pigs, are used to parametrize the model and, importantly, test the underlying assumptions. The model allows the relationship between within-host parameters and transmission to be determined explicitly through their influence on the reproduction number and generation time. Furthermore, these critical within-host parameters (time and level of peak titre, viral growth and clearance rates) can be computed from more complex within-host models, raising the possibility of assessing the impact of within-host processes on between-host transmission in a more detailed quantitative manner.

Laboratory testing and on-site storage are successful at mitigating the risk of release of foot-and-mouth disease virus via production of bull semen in the USA

Thousands of frozen bovine semen doses are produced daily in the US for domestic use. An incursion of foot-and-mouth disease (FMD) in the country would pose strong challenges to the movements of animals and animal products between premises. Secure supply plans require an estimation of the risk associated with target commodities and the effectiveness of mitigation measures. This study presents the results of a quantitative assessment of the risk of release of FMD virus from five of the largest commercial bull studs in the US via contaminated frozen processed semen. The methodology from a previous study was adapted to better fit the US production system and includes more recent data. Two models were combined, a deterministic compartmental model of FMD transmission and a stochastic risk assessment model. The compartmental model simulated an FMD outbreak within a collection facility, following the introduction of a latent-infected bull. The risk of release was defined as the annual likelihood of releasing at least one frozen semen batch, defined as the total amount of semen collected from a single bull on a given collection day, containing viable FMD virus. A scenario tree was built using nine steps leading from the collection to the release of a contaminated batch from a given facility. The first step, the annual probability of an FMD outbreak in a given facility, was modeled using an empirical distribution fitted to incidence data predicted by five models published between 2012 and 2022. An extra step was added to the previously published risk pathway, to account for routine serological or virological surveillance within facilities. The results showed that the mitigation measures included in the assessment were effective at reducing the risk of release. The median annual risk of release from the five facilities was estimated at less than 2 in 10 billion (1.5 x 10-10) in the scenario including a 30-day storage, routine genome detection assays performed every two weeks and RT-PCR testing of the semen. In this scenario, there was a 95% chance that the risk of release would be lower than 0.00041. This work provides strong support to the industry for improving their response plans to an incursion of FMD virus in the US.

An exploration of within-herd dynamics of a transboundary livestock disease: A foot and mouth disease case study

Transboundary livestock diseases are a high priority for policy makers because of the serious economic burdens associated with infection. In order to make well informed preparedness and response plans, policy makers often utilize mathematical models to understand possible outcomes of different control strategies and outbreak scenarios. Many of these models focus on the transmission between herds and the overall trajectory of the outbreak. While the course of infection within herds has not been the focus of the majority of models, a thorough understanding of within-herd dynamics can provide valuable insight into a disease system by providing information on herd-level biological properties of the infection, which can be used to inform decision making in both endemic and outbreak settings and to inform larger between-herd models. In this study, we develop three stochastic simulation models to study within-herd foot and mouth disease dynamics and the implications of different empirical data-based assumptions about the timing of the onset of infectiousness and clinical signs. We also study the influence of herd size and the proportion of the herd that is initially infected on the outcome of the infection. We find that increasing herd size increases the duration of infectiousness and that the size of the herd plays a more significant role in determining this duration than the number of initially infected cattle in that herd. We also find that the assumptions made regarding the onset of infectiousness and clinical signs, which are based on contradictory empirical findings, can result in the predictions about when infection would be detectable differing by several days. Therefore, the disease progression used to characterize the course of infection in a single bovine host could have significant implications for determining when herds can be detected and subsequently controlled; the timing of which could influence the overall predicted trajectory of outbreaks.

Analysis of cattle movement networks in Paraguay: Implications for the spread and control of infectious diseases

Beef exports represent a substantial part of Paraguay's agricultural sector. Cattle movements involve a high risk due to the possible spread of bovine diseases that can have a significant impact on the country's economy. We analyzed cattle movements from 2014 to 2018 using the networks analysis methodology at the holding and district levels at different temporal scales. We built two types of networks to identify network characteristics that may contribute to the spread of two diseases with different epidemiological characteristics: i) a network including all cattle movements to consider the transmission of a disease of rapid spread like foot and mouth disease, and ii) a network including only cow movements to account for bovine brucellosis, a disease of slow spread that occurs mainly in adult females. Network indicators did not vary substantially among the cattle and cow only networks. The holdings/districts included in the largest strongly connected components were distributed throughout the country. Percolation analysis performed at the holding level showed that a large number of holdings should be removed to make the largest strongly connected component disappear. Higher values of the centrality indicators were found for markets than for farms, indicating that they may play an important role in the spread of an infectious disease. At the holding level (but not at the district level), the networks exhibited characteristics of small-world networks. This property may facilitate the spread of foot and mouth disease in case of re-emergence, or of bovine brucellosis in the country through cattle movements. They should be taken into account when implementing surveillance or control measures for these diseases.

Viral dynamics and immune responses to foot-and-mouth disease virus in African buffalo (Syncerus caffer)

Foot-and-mouth disease (FMD) is one of the most important livestock diseases restricting international trade. While African buffalo (Syncerus caffer) act as the main wildlife reservoir, viral and immune response dynamics during FMD virus acute infection have not been described before in this species. We used experimental needle inoculation and contact infections with three Southern African Territories serotypes to assess clinical, virological and immunological dynamics for thirty days post infection. Clinical FMD in the needle inoculated buffalo was mild and characterised by pyrexia. Despite the absence of generalised vesicles, all contact animals were readily infected with their respective serotypes within the first two to nine days after being mixed with needle challenged buffalo. Irrespective of the route of infection or serotype, there were positive associations between the viral loads in blood and the induction of host innate pro-inflammatory cytokines and acute phase proteins. Viral loads in blood and tonsil swabs were tightly correlated during the acute phase of the infection, however, viraemia significantly declined after a peak at four days post-infection (dpi), which correlated with the presence of detectable neutralising antibodies. In contrast, infectious virus was isolated in the tonsil swabs until the last sampling point (30 dpi) in most animals. The pattern of virus detection in serum and tonsil swabs was similar for all three serotypes in the direct challenged and contact challenged animals. We have demonstrated for the first time that African buffalo are indeed systemically affected by FMD virus and clinical FMD in buffalo is characterized by a transient pyrexia. Despite the lack of FMD lesions, infection of African buffalo was characterised by high viral loads in blood and oropharynx, rapid and strong host innate and adaptive immune responses and high transmissibility.

Delays in Epidemic Outbreak Control Cost Disproportionately Large Treatment Footprints to Offset

Epidemic outbreak control often involves a spatially explicit treatment area (quarantine, inoculation, ring cull) that covers the outbreak area and adjacent regions where hosts are thought to be latently infected. Emphasis on space however neglects the influence of treatment timing on outbreak control. We conducted field and in silico experiments with wheat stripe rust (WSR), a long-distance dispersed plant disease, to understand interactions between treatment timing and area interact to suppress an outbreak. Full-factorial field experiments with three different ring culls (outbreak area only to a 25-fold increase in treatment area) at three different disease control timings (1.125, 1.25, and 1.5 latent periods after initial disease expression) indicated that earlier treatment timing had a conspicuously greater suppressive effect than the area treated. Disease spread computer simulations over a broad range of influential epidemic parameter values (R0, outbreak disease prevalence, epidemic duration) suggested that potentially unrealistically large increases in treatment area would be required to compensate for even small delays in treatment timing. Although disease surveillance programs are costly, our results suggest that treatments early in an epidemic disease outbreak require smaller areas to be effective, which may ultimately compensate for the upfront costs of proactive disease surveillance programs.

Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions

Infectious diseases in livestock are well-known to infect multiple hosts and persist through a combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic dynamics of diseases being introduced on farms with more than one susceptible host species. Here, we describe multi-host contact networks and elucidate the potential of disease spread through farms with multiple hosts. Four years of between-farm animal movement among all farms of a Brazilian state were described through a static and monthly snapshot of network representations. We developed a stochastic multilevel model to simulate scenarios in which infection was seeded into single host and multi-host farms to quantify disease spread potential, and simulate network-based control actions used to evaluate the reduction of secondarily infected farms. We showed that the swine network was more connected than cattle and small ruminants in both the static and monthly snapshots. The small ruminant network was highly fragmented, however, contributed to interconnecting farms, with other hosts acting as intermediaries throughout the networks. When a single host was initially infected, secondary infections were observed across farms with all other species. Our stochastic multi-host model demonstrated that targeting the top 3.25% of the farms ranked by degree reduced the number of secondarily infected farms. The results of the simulation highlight the importance of considering multi-host dynamics and contact networks while designing surveillance and preparedness control strategies against pathogens known to infect multiple species.

Endemic persistence of a highly contagious pathogen: Foot-and-mouth disease in its wildlife host

Extremely contagious pathogens are a global biosecurity threat because of their high burden of morbidity and mortality, as well as their capacity for fast-moving epidemics that are difficult to quell. Understanding the mechanisms enabling persistence of highly transmissible pathogens in host populations is thus a central problem in disease ecology. Through a combination of experimental and theoretical approaches, we investigated how highly contagious foot-and-mouth disease viruses persist in the African buffalo, which serves as their wildlife reservoir. We found that viral persistence through transmission among acutely infected hosts alone is unlikely. However, the inclusion of occasional transmission from persistently infected carriers reliably rescues the most infectious viral strain from fade-out. Additional mechanisms such as antigenic shift, loss of immunity, or spillover among host populations may be required for persistence of less transmissible strains.

Scientific Opinion on the assessment of the control measures for category A diseases of Animal Health Law: Foot and Mouth Disease

EFSA received a mandate from the European Commission to assess the effectiveness of some of the control measures against diseases included in the Category A list according to Regulation (EU) 2016/429 on transmissible animal diseases ('Animal Health Law'). This opinion belongs to a series of opinions where these control measures will be assessed, with this opinion covering the assessment of control measures for foot and mouth disease (FMD). In this opinion, EFSA and the AHAW Panel of experts review the effectiveness of: i) clinical and laboratory sampling procedures, ii) monitoring period and iii) the minimum radius of the protection and surveillance zones, and the minimum length of time the measures should be applied in these zones. The general methodology used for this series of opinions has been published elsewhere; nonetheless, the transmission kernels used for the assessment of the minimum radius of the protection zone of 3 km and of the surveillance zone of 10 km are shown. Several scenarios for which these control measures had to be assessed were designed and agreed prior to the start of the assessment. The monitoring period of 21 days was assessed as effective, and it was concluded that the protection and the surveillance zones comprise > 99% of the infections from an affected establishment if transmission occurred. Recommendations, provided for each of the scenarios assessed, aim to support the European Commission in the drafting of further pieces of legislation, as well as for plausible ad hoc requests in relation to FMD.

Using a participatory qualitative risk assessment to estimate the risk of introduction and spread of transboundary animal diseases in scarce-data environments: A Spatial Qualitative Risk Analysis applied to foot-and-mouth disease in Tunisia 2014-2019

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

Modeling Intervention Scenarios During Potential Foot-and-Mouth Disease Outbreaks Within U.S. Beef Feedlots

Foot-and-mouth disease (FMD) is a highly contagious disease of livestock and has severely affected livestock industries during the past two decades in previously FMD-free countries. The disease was eliminated in North America in 1953 but remains a threat for re-introduction. Approximately 44% of the on-feed beef cattle in the U.S. are concentrated in feedlots <32,000 heads, but little information is available on dynamics of FMD in large feedlots. Therefore, there is a need to explore possible management and intervention strategies that might be implemented during potential FMD outbreaks on feedlots. We used a within home-pen stochastic susceptible-latent-infectious-recovered (SLIR) FMD dynamics model nested in a meta-population model of home-pens in a feedlot. The combinatory model was previously developed to simulate foot-and-mouth disease virus (FMDv) transmission within U.S. beef feedlots. We evaluated three intervention strategies initiated on the day of FMD detection: stopping movements of cattle between home-pens and hospital-pen(s) (NH), barrier depopulation combined with NH (NH-BD), and targeted depopulation of at-risk home-pens combined with NH (NH-TD). Depopulation rates investigated ranged from 500 to 4,000 cattle per day. We evaluated the projected effectiveness of interventions by comparing them with the no-intervention FMD dynamics in the feedlot. We modeled a small-size (4,000 cattle), medium-size (12,000 cattle), and large-size (24,000 cattle) feedlots. Implementation of NH delayed the outbreak progression, but it did not prevent infection of the entire feedlot. Implementation of NH-BD resulted in depopulation of 50% of cattle in small- and medium-size feedlots, and 25% in large-size feedlots, but the intervention prevented infection of the entire feedlot in 40% of simulated outbreaks in medium-size feedlots, and in 8% in large-size feedlots. Implementation of NH-TD resulted in depopulation of up to 50% of cattle in small-size feedlots, 75% in medium-size feedlots, and 25% in large-size feedlots, but rarely prevented infection of the entire feedlot. Number of hospital-pens in the feedlot was shown to weakly impact the success of NH-TD. Overall, the results suggest that stopping cattle movements between the home-pens and hospital-pens, without or with barrier or targeted cattle depopulation, would not be highly effective to interrupt FMDv transmission within a feedlot.

A Meta-Population Model of Potential Foot-and-Mouth Disease Transmission, Clinical Manifestation, and Detection Within U.S. Beef Feedlots

Foot-and-mouth disease (FMD) has not been reported in the U.S. since 1929. Recent outbreaks in previously FMD-free countries raise concerns about potential FMD introductions in the U.S. Mathematical modeling is the only tool for simulating infectious disease outbreaks in non-endemic territories. In the majority of prior studies, FMD virus (FMDv) transmission on-farm was modeled assuming homogenous animal mixing. This assumption is implausible for U.S. beef feedlots which are divided into multiple home-pens without contact between home-pens except fence line with contiguous home-pens and limited mixing in hospital pens. To project FMDv transmission and clinical manifestation in a feedlot, we developed a meta-population stochastic model reflecting the contact structure. Within a home-pen, the dynamics were represented assuming homogenous animal mixing by a modified SLIR (susceptible-latent-infectious-recovered) model with four additional compartments tracing cattle with subclinical or clinical FMD and infectious status. Virus transmission among home-pens occurred via cattle mixing in hospital-pen(s), cowboy pen rider movements between home-pens, airborne, and for contiguous home-pens fence-line and via shared water-troughs. We modeled feedlots with a one-time capacity of 4,000 (small), 12,000 (medium), and 24,000 (large) cattle. Common cattle demographics, feedlot layout, endemic infectious and non-infectious disease occurrence, and production management were reflected. Projected FMD-outbreak duration on a feedlot ranged from 49 to 82 days. Outbreak peak day (with maximum number of FMD clinical cattle) ranged from 24 (small) to 49 (large feedlot). Detection day was 4-12 post-FMD-introduction with projected 28, 9, or 4% of cattle already infected in a small, medium, or large feedlot, respectively. Depletion of susceptible cattle in a feedlot occurred by day 23-51 post-FMD-introduction. Parameter-value sensitivity analyses were performed for model outputs. Detection occurred sooner if there was a higher initial proportion of latent animals in the index home-pen. Shorter outbreaks were associated with a shorter latent period and higher bovine respiratory disease morbidity (impacting the in-hospital-pen cattle mixing occurrence). This first model of potential FMD dynamics on U.S. beef feedlots shows the importance of capturing within-feedlot cattle contact structure for projecting infectious disease dynamics. Our model provides a tool for evaluating FMD outbreak control strategies.

Quantifying the Transmission of Foot-and-Mouth Disease Virus in Cattle via a Contaminated Environment

Effective control of a disease relies on comprehensive understanding of how transmission occurs, in order to design and apply effective control measures. Foot-and-mouth disease virus (FMDV) is primarily spread by direct contact between infected and naive individuals, although the high levels of virus shed by infected animals mean that virus can also be spread through contact with contaminated environments. Using a series of transmission experiments, we demonstrate that environmental transmission alone would be sufficient to sustain an outbreak. Key observations include that a risk of transmission exists before clinical signs of foot-and-mouth disease (FMD) are apparent in cattle and that survival of virus in the environment extends the transmission risk period. This study highlights the role a contaminated environment can play in the transmission of FMDV and presents approaches that can also be applied to study the transmission of other pathogens that are able to survive in the environment.

Indirect transmission via a contaminated environment can occur for a number of pathogens, even those typically thought of as being directly transmitted, such as influenza virus, norovirus, bovine tuberculosis, or foot-and-mouth disease virus (FMDV). Indirect transmission facilitates spread from multiple sources beyond the infectious host, complicating the epidemiology and control of these diseases. This study carried out a series of transmission experiments to determine the dose-response relationship between environmental contamination and transmission of FMDV in cattle from measurements of viral shedding and rates of environmental contamination and survival. Seven out of ten indirect exposures resulted in successful transmission. The basic reproduction number for environmental transmission of FMDV in this experimental setting was estimated at 1.65, indicating that environmental transmission alone could sustain an outbreak. Importantly, detection of virus in the environment prior to the appearance of clinical signs in infected cattle and successful transmission from these environments highlights there is a risk of environmental transmission even before foot-and-mouth disease (FMD) is clinically apparent in cattle. Estimated viral decay rates suggest that FMDV remained viable in this environment for up to 14 days, emphasizing the requirement for stringent biosecurity procedures following outbreaks of FMD and the design of control measures that reflect the biology of a pathogen.

Multilevel model for airborne transmission of foot-and-mouth disease applied to Swedish livestock

The foot-and-mouth disease is an ever-present hazard to the livestock industry due to the huge economic consequences following an outbreak that necessitates culling of possibly infected animals in vast numbers. The disease is highly contagious and previous epizootics have shown that it spreads by many routes. One such route is airborne transmission, which has been investigated in this study by means of a detailed multilevel model that includes all scales of an outbreak. Local spread within an infected farm is described by a stochastic compartment model while the spread between farms is quantified by atmospheric dispersion simulations using a network representation of the set of farms. The model was applied to the Swedish livestock industry and the risk for an epizootic outbreak in Sweden was estimated using the basic reproduction number of each individual livestock-holding farm as the endpoint metric. The study was based on comprehensive official data sets for both the current livestock holdings and regional meteorological conditions. Three species of farm animals are susceptible to the disease and are present in large numbers: cattle, pigs and sheep. These species are all included in this study using their individual responses and consequences to the disease. It was concluded that some parts of southern Sweden are indeed preconditioned to harbor an airborne epizootic, while the sparse farm population of the north renders such events unlikely to occur there. The distribution of the basic reproduction number spans over several orders of magnitudes with low risk of disease spread from the majority of the farms while some farms may act as very strong disease transmitters. The results may serve as basic data in the planning of the national preparedness for this type of events.

Modeling the Transmission of Foot and Mouth Disease to Inform Transportation of Infected Carcasses to a Disposal Site During an Outbreak Event

In the event of a Food and Mouth Disease (FMD) outbreak in the United States, an infected livestock premises is likely to result in a high number of carcasses (swine and/or cattle) as a result of depopulation. If relocating infected carcasses to an off-site disposal site is allowed, the virus may have increased opportunity to spread to uninfected premises and result in exposure of susceptible livestock. A stochastic within-herd disease spread model was used to predict the time to detect the disease by observation of clinical signs within the herd, and the number of animals in different disease stages over time. Expert opinion was elicited to estimate depopulation parameters in various scenarios. Disease detection was assumed when 5% of the population showed clinical signs by direct observation. Time to detection (5 and 95th percentile values) was estimated for all swine farm sizes (500-10,000 head) ranged from 102 to 282 h, from 42 to 216 h for all dairy cattle premises sizes (100-2,000 head) and from 66 to 240 h for all beef cattle premises sizes (5,000-50,000 head). Total time from infection to beginning depopulation (including disease detection and confirmation) for the first FMD infected case was estimated between 8.5-14.3 days for swine, 6-12.8 days for dairy or beef cattle premises. Total time estimated for subsequent FMD cases was between 6.8-12.3 days for swine, 4.3-10.8 days for dairy and 4.5-10.5 days for beef cattle premises. On an average sized operation, a sizable proportion of animals in the herd (34-56% of swine, 48-60% of dairy cattle, and 47-60% of beef cattle for the first case and 49-60% of swine, 55-60% of dairy cattle, 56-59% of beef cattle for subsequent cases) would be viremic at the time of beginning depopulation. A very small fraction of body fluids from the carcasses (i.e., 1 mL) would contain virus that greatly exceeds the minimum infectious dose by oral (4-7x) or inhalation (7-13x) route for pigs and cattle.

Planning "Plan B": The Case of Moving Cattle From an Infected Feedlot Premises During a Hypothetical Widespread FMD Outbreak in the United States

In the event of a foot-and-mouth disease (FMD) outbreak in the United States, "stamping out" FMD infected premises has been proposed as the method of choice for the control of outbreaks. However, if a widespread, catastrophic FMD outbreak in the U.S. were to occur, alternative solutions to stamping out may be required, particularly for large feedlots with over 10,000 cattle. Such strategies include moving cattle from infected or not known to be infected operations to slaughter facilities either with or without prior implementation of vaccination. To understand the risk of these strategies, it is important to estimate levels of herd viremia. Multiple factors must be considered when determining risk and feasibility of moving cattle from a feedlot to a slaughter facility during an FMD outbreak. In addition to modeling within-herd disease spread to estimate prevalence of viremic animals, we explore potential pathways for viral spread associated with the movement of asymptomatic beef cattle (either pre-clinical or recovered) from an infected feedlot premises to offsite harvest facilities. This analysis was proactive in nature, however evaluation of the likelihood of disease spread relative to disease (infection) phase, time of movement, and vaccination status are all factors which should be considered in managing and containing a large-scale FMD outbreak in the United States.

Multi-scale dynamics of infectious diseases

To address the challenge of multiscale dynamics of infectious diseases, the Mathematical Biosciences Institute organized a workshop at The Ohio State University to bring together scientists from a variety of disciplines to share expertise gained through looking at infectious diseases across different scales. The researchers at the workshop, held in April 2018, were specifically looking at three model systems: foot-and-mouth disease, vector-borne diseases and enteric diseases. Although every multiscale model must be necessarily derived from a multiscale system, not every multiscale system has to lead to multiscale models. These three model systems seem to have produced a variety of both multiscale and integrated single-scale mechanistic models that have developed their own strengths and particular challenges. Here, we present papers from some of the workshop participants to show the breadth of the field.

African Swine Fever: Fast and Furious or Slow and Steady?

Since the introduction of African swine fever (ASF) into Georgia in 2007, the disease has been spreading in an unprecedented way. Many countries that are still free from the disease fear the emergence of ASF in their territory either in domestic pigs or in wild boar. In the past, ASF was often described as being a highly contagious disease with mortality often up to 100%. However, the belief that the disease might enter a naïve population and rapidly affect the entire susceptible population needs to be critically reviewed. The current ASF epidemic in wild boar, but also the course of ASF within outbreaks in domestic pig holdings, suggest a constant, but relatively slow spread. Moreover, the results of several experimental and field studies support the impression that the spread of ASF is not always fast. ASF spread and its speed depend on various factors concerning the host, the virus, and also the environment. Many of these factors and their effects are not fully understood. For this review, we collated published information regarding the spreading speed of ASF and the factors that are deemed to influence the speed of ASF spread and tried to clarify some issues and open questions in this respect.

Modeling the role of carrier and mobile herds on foot-and-mouth disease virus endemicity in the Far North Region of Cameroon

Foot and mouth disease virus (FMDV) is an RNA virus that infects cloven-hoofed animals, often produces either epidemic or endemic conditions, and negatively affects agricultural economies worldwide. FMDV epidemic dynamics have been extensively studied, but understanding of drivers of disease persistence in areas in which FMDV is endemic, such as most of sub-Saharan Africa, is lacking. We present a spatial stochastic model of disease dynamics that incorporates a spatial transmission kernel in a modified Gillespie algorithm, and use it to evaluate two hypothesized drivers of endemicity: asymptomatic carriers and the movement of mobile herds. The model is parameterized using data from the pastoral systems in the Far North Region of Cameroon. Our computational study provides evidence in support of the hypothesis that asymptomatic carriers, but not mobile herds, are a driver of endemicity.

Understanding the transmission of foot-and-mouth disease virus at different scales

Foot-and-mouth disease (FMD) is highly infectious, but despite the large quantities of FMD virus released into the environment and the extreme susceptibility of host species to infection, transmission is not always predictable. Whereas virus spread in endemic settings is characterised by frequent direct and indirect animal contacts, incursions into FMD-free countries may be seeded by low-probability events such as fomite or wind-borne aerosol routes. There remains a void between data generated from small-scale experimental studies and our ability to reliably reconstruct transmission routes at different scales between farms, countries and regions. This review outlines recent transmission studies in susceptible host species, and considers new approaches that integrate virus genomics and epidemiological data to recreate and understand the spread of FMD.

Foot-and-mouth disease virus transmission dynamics and persistence in a herd of vaccinated dairy cattle in India

Foot-and-mouth disease (FMD) is an important transboundary disease with substantial economic impacts. Although between-herd transmission of the disease has been well studied, studies focusing on within-herd transmission using farm-level outbreak data are rare. The aim of this study was to estimate parameters associated with within-herd transmission, host physiological factors and FMD virus (FMDV) persistence using data collected from an outbreak that occurred at a large, organized dairy farm in India. Of 1,836 regularly vaccinated, adult dairy cattle, 222 had clinical signs of FMD over a 39-day period. Assuming homogenous mixing, a frequency-dependent compartmental model of disease transmission was built. The transmission coefficient and basic reproductive number were estimated to be between 16.2-18.4 and 67-88, respectively. Non-pregnant animals were more likely to manifest clinical signs of FMD as compared to pregnant cattle. Based on oropharyngeal fluid (probang) sampling and FMDV-specific RT-PCR, four of 36 longitudinally sampled animals (14%) were persistently infected carriers 10.5 months post-outbreak. There was no statistical difference between subclinical and clinically infected animals in the duration of the carrier state. However, prevalence of NSP-ELISA antibodies differed significantly between subclinical and clinically infected animals 12 months after the outbreak with 83% seroprevalence amongst clinically infected cattle compared to 69% of subclinical animals. This study further elucidates within-herd FMD transmission dynamics during the acute-phase and characterizes duration of FMDV persistence and seroprevalence of FMD under natural conditions in an endemic setting.

Bayesian inference of epidemiological parameters from transmission experiments

Epidemiological parameters for livestock diseases are often inferred from transmission experiments. However, there are several limitations inherent to the design of such experiments that limits the precision of parameter estimates. In particular, infection times and latent periods cannot be directly observed and infectious periods may also be censored. We present a Bayesian framework accounting for these features directly and employ Markov chain Monte Carlo techniques to provide robust inferences and quantify the uncertainty in our estimates. We describe the transmission dynamics using a susceptible-exposed-infectious-removed compartmental model, with gamma-distributed transition times. We then fit the model to published data from transmission experiments for foot-and-mouth disease virus (FMDV) and African swine fever virus (ASFV). Where the previous analyses of these data made various assumptions on the unobserved processes in order to draw inferences, our Bayesian approach includes the unobserved infection times and latent periods and quantifies them along with all other model parameters. Drawing inferences about infection times helps identify who infected whom and can also provide insights into transmission mechanisms. Furthermore, we are able to use our models to measure the difference between the latent periods of inoculated and contact-challenged animals and to quantify the effect vaccination has on transmission.

Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks

Whole-genome sequencing of pathogens from host samples becomes more and more routine during infectious disease outbreaks. These data provide information on possible transmission events which can be used for further epidemiologic analyses, such as identification of risk factors for infectivity and transmission. However, the relationship between transmission events and sequence data is obscured by uncertainty arising from four largely unobserved processes: transmission, case observation, within-host pathogen dynamics and mutation. To properly resolve transmission events, these processes need to be taken into account. Recent years have seen much progress in theory and method development, but existing applications make simplifying assumptions that often break up the dependency between the four processes, or are tailored to specific datasets with matching model assumptions and code. To obtain a method with wider applicability, we have developed a novel approach to reconstruct transmission trees with sequence data. Our approach combines elementary models for transmission, case observation, within-host pathogen dynamics, and mutation, under the assumption that the outbreak is over and all cases have been observed. We use Bayesian inference with MCMC for which we have designed novel proposal steps to efficiently traverse the posterior distribution, taking account of all unobserved processes at once. This allows for efficient sampling of transmission trees from the posterior distribution, and robust estimation of consensus transmission trees. We implemented the proposed method in a new R package phybreak. The method performs well in tests of both new and published simulated data. We apply the model to five datasets on densely sampled infectious disease outbreaks, covering a wide range of epidemiological settings. Using only sampling times and sequences as data, our analyses confirmed the original results or improved on them: the more realistic infection times place more confidence in the inferred transmission trees.

It is becoming easier and cheaper to obtain (whole genome) sequences of pathogen samples during outbreaks of infectious diseases. If all hosts during an outbreak are sampled, and these samples are sequenced, the small differences between the sequences (single nucleotide polymorphisms, SNPs) give information on the transmission tree, i.e. who infected whom, and when. However, correctly inferring this tree is not straightforward, because SNPs arise from unobserved processes including infection events, as well as pathogen growth and mutation within the hosts. Several methods have been developed in recent years, but often for specific applications or with limiting assumptions, so that they are not easily applied to new settings and datasets. We have developed a new model and method to infer transmission trees without putting prior limiting constraints on the order of unobserved events. The method is easily accessible in an R package implementation. We show that the method performs well on new and previously published simulated data. We illustrate applicability to a wide range of infectious diseases and settings by analysing five published datasets on densely sampled infectious disease outbreaks, confirming or improving the original results.

Impact of Network Activity on the Spread of Infectious Diseases through the German Pig Trade Network

The trade of livestock is an important and growing economic sector, but it is also a major factor in the spread of diseases. The spreading of diseases in a trade network is likely to be influenced by how often existing trade connections are active. The activity α is defined as the mean frequency of occurrences of existing trade links, thus 0 < α ≤ 1. The observed German pig trade network had an activity of α = 0.11, thus each existing trade connection between two farms was, on average, active at about 10% of the time during the observation period 2008–2009. The aim of this study is to analyze how changes in the activity level of the German pig trade network influence the probability of disease outbreaks, size, and duration of epidemics for different disease transmission probabilities. Thus, we want to investigate the question, whether it makes a difference for a hypothetical spread of an animal disease to transport many animals at the same time or few animals at many times. A SIR model was used to simulate the spread of a disease within the German pig trade network. Our results show that for transmission probabilities <1, the outbreak probability increases in the case of a decreased frequency of animal transports, peaking range of α from 0.05 to 0.1. However, for the final outbreak size, we find that a threshold exists such that finite outbreaks occur only above a critical value of α, which is ~0.1, and therefore in proximity of the observed activity level. Thus, although the outbreak probability increased when decreasing α, these outbreaks affect only a small number of farms. The duration of the epidemic peaks at an activity level in the range of α = 0.2–0.3. Additionally, the results of our simulations show that even small changes in the activity level of the German pig trade network would have dramatic effects on outbreak probability, outbreak size, and epidemic duration. Thus, we can conclude and recommend that the network activity is an important aspect, which should be taken into account when modeling the spread of diseases within trade networks.

Quantitative effects of a declaration of a state of emergency on foot-and-mouth disease

OBJECTIVES

The law in Japan requires the declaration of a state of emergency and implementation of countermeasures for an epidemic of a new infectious disease. However, because a state of emergency has never been declared in Japan, its effects remain unknown. The required countermeasures are similar to those implemented in the foot-and-mouth disease epidemic in Miyazaki in 2010. This study aimed to quantitatively estimate the effect of the declaration in 2010 and investigate the nature of the epidemic based on the day on which the declaration took effect.

METHODS

Only publicly available data were used. Data for farms in the most affected town were analyzed. A modified susceptible-infected-recovered model was used to estimate the effect and for the simulation. Another model was used to estimate the effective reproduction number.

RESULTS

After the declaration, the intra-bovine transmission rate decreased by 18.1 %, and there were few days when the effective reproduction number was >1.0. A few weeks delay in the declaration significantly increased the possibility of epidemic, number of farms at peak, and final infection scale.

CONCLUSIONS

Based on the substantial decrease in the transmission rate after the declaration of a state of emergency in 2010, a future declaration will have a similar effect for a new infectious disease even though a direct extrapolation is not valid. Although a declaration should be carefully considered owing to the potential socioeconomic effects, it is essential to prepare for the implementation given that a delay of only a few weeks should be acceptable.

Data-Driven Models of Foot-and-Mouth Disease Dynamics: A Review

Foot-and-mouth disease virus (FMDV) threatens animal health and leads to considerable economic losses worldwide. Progress towards minimizing both veterinary and financial impact of the disease will be made with targeted disease control policies. To move towards targeted control, specific targets and detailed control strategies must be defined. One approach for identifying targets is to use mathematical and simulation models quantified with accurate and fine-scale data to design and evaluate alternative control policies. Nevertheless, published models of FMDV vary in modelling techniques and resolution of data incorporated. In order to determine which models and data sources contain enough detail to represent realistic control policy alternatives, we performed a systematic literature review of all FMDV dynamical models that use host data, disease data or both data types. For the purpose of evaluating modelling methodology, we classified models by control strategy represented, resolution of models and data, and location modelled. We found that modelling methodology has been well developed to the point where multiple methods are available to represent detailed and contact-specific transmission and targeted control. However, detailed host and disease data needed to quantify these models are only available from a few outbreaks. To address existing challenges in data collection, novel data sources should be considered and integrated into models of FMDV transmission and control. We suggest modelling multiple endemic areas to advance local control and global control and better understand FMDV transmission dynamics. With incorporation of additional data, models can assist with both the design of targeted control and identification of transmission drivers across geographic boundaries.

Serotype-Specific Transmission and Waning Immunity of Endemic Foot-and-Mouth Disease Virus in Cameroon

Foot-and-mouth disease virus (FMDV) causes morbidity and mortality in a range of animals and threatens local economies by acting as a barrier to international trade. The outbreak in the United Kingdom in 2001 that cost billions to control highlighted the risk that the pathogen poses to agriculture. In response, several mathematical models have been developed to parameterize and predict both transmission dynamics and optimal disease control. However, a lack of understanding of the multi-strain etiology prevents characterization of multi-strain dynamics. Here, we use data from FMDV serology in an endemic setting to probe strain-specific transmission and immunodynamics. Five serotypes of FMDV affect cattle in the Far North Region of Cameroon. We fit both catalytic and reverse catalytic models to serological data to estimate the force of infection and the rate of waning immunity, and to detect periods of sustained transmission. For serotypes SAT2, SAT3, and type A, a model assuming life-long immunity fit better. For serotypes SAT1 and type O, the better-fit model suggests that immunity may wane over time. Our analysis further indicates that type O has the greatest force of infection and the longest duration of immunity. Estimates for the force of infection were time-varying and indicated that serotypes SAT1 and O displayed endemic dynamics, serotype A displayed epidemic dynamics, and SAT2 and SAT3 did not sustain local chains of transmission. Since these results were obtained from the same population at the same time, they highlight important differences in transmission specific to each serotype. They also show that immunity wanes at rates specific to each serotype, which influences patterns of local persistence. Overall, this work shows that viral serotypes can differ significantly in their epidemiological and immunological characteristics. Patterns and processes that drive transmission in endemic settings must consider complex viral dynamics for accurate representation and interpretation.

Modeling two strains of disease via aggregate-level infectivity curves

Well formulated models of disease spread, and efficient methods to fit them to observed data, are powerful tools for aiding the surveillance and control of infectious diseases. Our project considers the problem of the simultaneous spread of two related strains of disease in a context where spatial location is the key driver of disease spread. We start our modeling work with the individual level models (ILMs) of disease transmission, and extend these models to accommodate the competing spread of the pathogens in a two-tier hierarchical population (whose levels we refer to as 'farm' and 'animal'). The postulated interference mechanism between the two strains is a period of cross-immunity following infection. We also present a framework for speeding up the computationally intensive process of fitting the ILM to data, typically done using Markov chain Monte Carlo (MCMC) in a Bayesian framework, by turning the inference into a two-stage process. First, we approximate the number of animals infected on a farm over time by infectivity curves. These curves are fit to data sampled from farms, using maximum likelihood estimation, then, conditional on the fitted curves, Bayesian MCMC inference proceeds for the remaining parameters. Finally, we use posterior predictive distributions of salient epidemic summary statistics, in order to assess the model fitted.

Within herd transmission and evaluation of the performance of clinical and serological diagnosis of foot-and-mouth disease in partially immune cattle herds

The control of foot-and-mouth disease (FMD) in vaccinated populations relies upon surveillance activities such as clinical inspections (CI) and serological monitoring. New evidence to refine current surveillance guidelines has been provided by evaluating (1) the diagnostic performance of CI and serological tests for detection of FMD virus (FMDV) non-structural proteins (NSP), and (2) the within-herd transmission of the virus in partially immune cattle. Data came from 23 affected herds during an epidemic of FMDV type O in Bolivia, in 2007. All cattle (n=957) in these herds were clinically inspected and serum samples were collected one month after the last animal with clinical signs was detected. Samples were tested for the presence of antibodies against NSP using the PANAFTOSA 3ABC-ELISA test and a subset of samples were tested using the enzyme-linked immunoelectrotransfer blot assay (EITB). Data from clinical and serological diagnoses were analysed using a Bayesian model. The sensitivity Se and specificity Sp of the tests, as well as the prevalence and the within-herd reproduction ratio R of FMDV were estimated. In addition, risk factors for infection were identified. The Se of CI, the 3ABC-ELISA and the EITB tests were estimated to be 0.30, 0.88 and 0.96 respectively. The estimated Sp, in the same order, were 0.88, 0.93 and 0.97. The within-herd prevalence of infected animals ranged from 0.04 to 0.91 and R ranged from 1.02 to 2.68. It was observed that cattle coming from areas with high vaccination coverage had a lower risk of becoming infected than home-bred cattle from the affected herds, where vaccination coverage was thought to be low. Although these estimates come from herds kept under specific conditions, they provide a reference for future surveillance design and can inform simulation models for surveillance and control of FMD in similar cattle populations.

Highly dynamic animal contact network and implications on disease transmission

Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R₀ < 2).

Supersize me: how whole-genome sequencing and big data are transforming epidemiology

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Whole-genome sequencing is used for forensic epidemiology.

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Big data can transform forensic epidemiology.

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Clustering, biases, wildlife reservoirs, and emerging infections can all be addressed.

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Phylodynamics approaches to integrate epidemiological and evolutionary data have been highly successful but still face scientific challenges.

In epidemiology, the identification of ‘who infected whom’ allows us to quantify key characteristics such as incubation periods, heterogeneity in transmission rates, duration of infectiousness, and the existence of high-risk groups. Although invaluable, the existence of many plausible infection pathways makes this difficult, and epidemiological contact tracing either uncertain, logistically prohibitive, or both. The recent advent of next-generation sequencing technology allows the identification of traceable differences in the pathogen genome that are transforming our ability to understand high-resolution disease transmission, sometimes even down to the host-to-host scale. We review recent examples of the use of pathogen whole-genome sequencing for the purpose of forensic tracing of transmission pathways, focusing on the particular problems where evolutionary dynamics must be supplemented by epidemiological information on the most likely timing of events as well as possible transmission pathways. We also discuss potential pitfalls in the over-interpretation of these data, and highlight the manner in which a confluence of this technology with sophisticated mathematical and statistical approaches has the potential to produce a paradigm shift in our understanding of infectious disease transmission and control.

A Bayesian framework to assess the potential for controlling classical scrapie in sheep flocks using a live diagnostic test

Current strategies to control classical scrapie remove animals at risk of scrapie rather than those known to be infected with the scrapie agent. Advances in diagnostic tests, however, suggest that a more targeted approach involving the application of a rapid live test may be feasible in future. Here we consider the use of two diagnostic tests: recto-anal mucosa-associated lymphatic tissue (RAMALT) biopsies; and a blood-based assay. To assess their impact we developed a stochastic age- and prion protein (PrP) genotype-structured model for the dynamics of scrapie within a sheep flock. Parameters were estimated in a Bayesian framework to facilitate integration of a number of disparate datasets and to allow parameter uncertainty to be incorporated in model predictions. In small flocks a control strategy based on removal of clinical cases was sufficient to control disease and more stringent measures (including the use of a live diagnostic test) did not significantly reduce outbreak size or duration. In medium or large flocks strategies in which a large proportion of animals are tested with either live diagnostic test significantly reduced outbreak size, but not always duration, compared with removal of clinical cases. However, the current Compulsory Scrapie Flocks Scheme (CSFS) significantly reduced outbreak size and duration compared with both removal of clinical cases and all strategies using a live diagnostic test. Accordingly, under the assumptions made in the present study there is little benefit from implementing a control strategy which makes use of a live diagnostic test.

Epidemiology of the Foot-and-Mouth Disease Serotype O Epidemic of November 2010 to April 2011 in the Republic Of Korea

The largest epidemic of foot-and-mouth disease (FMD) in Korea since the first record in 1911 occurred between November 2010 and April 2011. The outbreak was confirmed in 153 farms, and more than three million animals were destroyed. This study presents the temporal and spatial distribution patterns, epidemiological investigation and the control measures for the 2010/2011 epidemic in Korea. The index case of this 2010/2011 FMD epidemic was reported in a pig-farming complex with five piggeries in Andong, GyeongBuk Province, on 28 November 2010, and the outbreak lasted 145 days. The largest number of new detection of the infected farms per day was recorded in mid-January. Epidemiological investigation revealed that the FMD virus had spread from farm to farm through routine movements associated with animal husbandry operations. In contrast to FMD epidemics in other countries in which movement of the infected animals largely contributed to the spread of the disease, human behaviours were major factors in the spread of the FMD virus in the Korean epidemic. The 2010/2011 epidemic was first confirmed in a local small and medium city where share of smallholder producers is higher than that of other provinces. Although Korea had a well-developed emergent response system with the experience of controlling infection and re-obtaining FMD-free status after the previous epidemics, Korea was prompted to revise their contingency plan by tailoring it to its unique livestock environment. Practical contingency plans tailored to Korea for control of FMD can be fully effective when farmers, livestock-related agencies, veterinary service providers and the general public work together.